FIRE: fractal indexing with robust extensions for image databases.

FIRE: fractal indexing with robust extensions for image databases. Research Abstract Details 

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FIRE: fractal indexing with robust extensions for image databases. Abstract Text:

R Distasi,M Nappi,M Tucci,

As already documented in the literature, fractal image encoding is a family of techniques that achieves a good compromise between compression and perceived quality by exploiting the self-similarities present in an image. Furthermore, because of its compactness and stability, the fractal approach can be used to produce a unique signature, thus obtaining a practical image indexing system. Since fractal-based indexing systems are able to deal with the images in compressed form, they are suitable for use with large databases. We propose a system called FIRE, which is then proven to be invariant under three classes of pixel intensity transformations and under geometrical isometries such as rotations by multiples of /spl pi//2 and reflections. This property makes the system robust with respect to a large class of image transformations that can happen in practical applications: the images can be retrieved even in the presence of illumination and/or color alterations. Additionally, the experimental results show the effectiveness of FIRE in terms of both compression and retrieval accuracy.

FIRE: fractal indexing with robust extensions for image databases. Publishing Authors By Initials

R Distasi,M Nappi,M Tucci,

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FIRE: fractal indexing with robust extensions for image databases. Journal Published:

PUBLICATION TYPE: Journal Article

Journal: IEEE transactions on image processing : a publicat

VOLUME: 12

Page Numbers: 373-84

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ISSN: 1057-7149

DAY: 1

MONTH: 02

YEAR: 2003

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LANGUAGE: eng

NlmUniqueID: 9886191

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Grant and Affiliation Information for FIRE: fractal indexing with robust extensions for image databases.

AFFILIATION: Dipt. di Matematica e Informatica, Univ. di Salerno, Baronissi, Italy.

Country: United States

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MEDLINETA: IEEE Trans Image Process

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